#
backtesting-engine
Here are 12 public repositories matching this topic...
A stock backtesting engine written in modern Java. And a pairs trading (cointegration) strategy implementation using a bayesian kalman filter model
java
finance
trading
stock
quantitative-finance
kalman-filter
backtest
quantitative-trading
cointegration
backtesting-engine
pairs-trading
cointegration-strategy
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Jul 28, 2019 - Java
Open
Documentation
2
dysonance
commented
Oct 26, 2017
Need to write more thorough documentation for package functionality.
- Examples
- Full walkthrough
- Universe data gathering usage
- New infix operators
- Crossover alias (up arrow)
- Crossunder alias (down arrow)
Option and stock backtester / live trader
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Feb 8, 2019 - Python
backtrader documentation
python
documentation
trading
trading-platform
trading-strategies
trading-algorithms
backtesting-trading-strategies
backtesting-engine
backtesting
backtesting-frameworks
trading-
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May 18, 2019
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May 27, 2019 - Go
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Jun 3, 2020 - JavaScript
Algotrading framework for C++17
c-plus-plus
finance
framework
trading
cpp
fintech
stock-market
algotrading
cpp17
c-plus-plus-17
stocks
futures
algorithmic-trading
backtesting-trading-strategies
backtest
backtesting-engine
backtesting
futures-market
algotrading-framework
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Updated
Apr 1, 2020 - C++
A pluggable automated trading system backtesting engine.
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Apr 19, 2019 - C#
Trading system that aims to buy stocks when they are low and sell stock when they have risen. The time horizon for trades is 2 - 45 days. The strategy has been successfully backtested in version 0.2. Next step: forward test strategy to ensure that it works in practice. Test RL to see if we can can improve results (currently only ~ 5 % of max.)
statistics
trading
threshold
curve
strategy
stocks
trade
buying
backtesting-engine
day
backtesting
savgol
yfinance
sell-pairs
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Jun 3, 2020 - Jupyter Notebook
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Updated
Nov 1, 2019 - TypeScript
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Expected Behavior
Is there an elegant and simple way to visualize a few trading models plotted on 1 chart? In fact a lot of projects like mine are centered around comparing various models (and even groups of models), so that would be handy to have a sugary way around this process, so: